Maximising net economic returns in mixed fisheries: how many species do we need to control?

Transcription

1 Maximising net economic returns in mixed fisheries: how many species do we need to control? Trevor Hutton, Sean Pascoe, James Innes, Satoshi Yamazaki and Tom Kompas Contributed presentation at the 60th AARES Annual Conference, Canberra, ACT, 2-5 February 2016 Copyright 2016 by Author(s). All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.

2 Maximising net economic returns in mixed fisheries: how many species do we need to control? Trevor Hutton, Sean Pascoe, James Innes, Satoshi Yamazaki and Tom Kompas AARES 2016: Canberra, Australia OCEANS AND ATMOSPHERE

3 Key issues to be looked at in the study How do you identify MEY (maximum economic yield) for different species in multispecies and multi-fleet fisheries? How different are dynamic estimates of MEY to static estimates? In multispecies fisheries characterised by technical interactions, do we need to control the catch of all species? If not, how many? How does bycatch and byproducts affect our estimates of MEY for target species? If we set a price on bycatch (e.g. seals, seabirds, dolphins), what does this do to our targets?

4 Approach Model based on Southern and Eastern Shark and Scalefish Fishery (SESSF) developed in an earlier study to assess proxy target reference points in multispecies fisheries Static equilibrium optimisation model Dynamic optimisation model Model to be updated and expanded to allow for some of these issues to be addressed Work still in progress Combination of optimisation and simulation approaches to be used to test different harvest strategies Aim of this presentation is to present the model as it currently stands, and what some of the results indicate Preliminary results not for citation as may change

5 Outline of the remainder of the talk Overview of MEY in single species and multispecies fisheries Description of the bioeconomic model Some earlier results Relationship between B MEY and B MSY Comparison of static and dynamic equilibrium levels of biomass (B) Where to next Preliminary results not for citation as may change

6 Sustainable revenue Sustianable yield MEY: Classic fisheries bio-economic models Equilibrium derivation Schaefer formulation Fox Schaefer (a) Fox formulation MSY know where it is, and corresponding B msy Biomass Cost (b) E mey lower than E msy Revert back to top graph ~ B mey > B msy (but by what factor?) ~ 1.2! Maximising net economic returns in mixed fisheries Fox Schaefer Effort

7 Revenue, profit, costs Revenue, costs Multi-species Reference Points 25 Can be sub-optimal The Multi-species MSY (and MEY) is not on par with single species Species 1 Species 2 Species 3 Species 4 cost MEY depends on revenue share What is a species MEY (stated as B mey in a multi-species fishery?) Effort revenue profit cost 5 Maximising net economic returns in mixed fisheries Effort

8 Specification of models Schaefer Fox logistic growth exponential growth Objective Function C - catch (yield), K - carrying capacity (B 0 ), E - effort, q - catchability coefficient (major technical interaction term), r - growth rate (very species specific) Pi - Profit, p-price, c - cost Maximising net economic returns in mixed fisheries

9 Current model: Trawl sector of SESSF Southern and Eastern Shark and Scalefish Fishery Two types of vessel (Otter trawl and Danish seine) Markets: Sydney and Melbourne 20 + species landed Flathead, Ling, Whiting, Silver warehou, John Dory, Morwong, Silver trevally Flathead contributed $14.6 million, Pink Ling $6.6 million and Silver warehou $2 million. Maximising net economic returns in mixed fisheries

10 Features of the model Catch effort models based on fox model Parameters estimated dynamically over a 20+ year period Catchability of each defined spatially and by gear type Four regions Two gears Six metiers Technical interactions captured by deriving fishing mortality spatially based on effort levels of each gear type and catchability coefficients Model is limited only to species that are caught jointly Excludes blue grenadier, orange roughy and other highly targetable species Preliminary results not for citation as may change

11 Biological parameters + price Growth (r) Carrying capacity (K) Price (p) Blue Warehou Flathead Gemfish John Dory Ling Mirror Dory Morwong East Morwong- West Ocean Perch Ribaldo Silver Warehou Silver Trevally Whiting Other species Maximising net economic returns in mixed fisheries

12 Fleet structure (6 metiers) Trawlers operating in Shelf trawl Eden to Sydney (NSW) Shelf trawl Eastern Bass Strait (EBS) Offshore - NSW Offshore EBS Danish seiners operating in Bass Strait (west of Lakes Entrance) Eastern Bass Strait (east of Lakes Entrance, Eden to NE Tas) (EBS) Multi-species economic reference points

13 Parameterisation economic Effort is measured per shot Vessel costs converted to unit cost/per shot Metier Fuel cost ($/shot) Vessel costs ($/shot) Crew share Freight Original Shelf trawl NSW Offshore trawl NSW Shelf trawl EBS Offshore trawl EBS Danish Seine Bass Strait Danish Seine EBS Maximising net economic returns in mixed fisheries

14 RESULTS: Case study equilibrium estimates of B mey /B msy 1.2 Multi-species economic reference points

15 Dynamic results Example of 1 run

16 Blue Warehou Flathead Gemfish John Dory Ling Mirror Dory Morwong East Morwong West Ocean Perch Ribaldo Silver Warehou Silver Trevally Whiting Biomass (tonnes) Biomass estimates (equilibrium versus dynamic) Equilibrium Dynamic Multi-species economic reference points

17 Main findings Results indicate: Default proxy target reference point of B mey = 1.2 B msy is not appropriate in multi-species fisheries Problematic to achieve multiple targets simultaneously Many species contribute small amount to revenue share (byproduct species) Potentially better to indirectly control impact on them (byproduct species) via controlling only the major species in terms of revenue shares Maximising net economic returns in mixed fisheries

18 Future work Plans for re-developed model to facilitate operationalisation: Consider short run versus long run dynamics Plus account for multi-fleet (metier) sub-optimal conditions Include bycatch (non-commercial: negative prices penalty) Include up-to-date costs and prices (and estimates of productivity) Include price-quantity (demand) relationships Run scenario simulations: varying number of species controlled Maximising net economic returns in mixed fisheries

19 Dynamic results Example of 1 run

20 Future work Plans for re-developed model to facilitate operationalisation: Consider short run versus long run dynamics Plus account for multi-fleet (metier) sub-optimal conditions Include bycatch (non-commercial: negative prices penalty) Include up-to-date costs and prices (and estimates of productivity) Include price-quantity (demand) relationships Run scenario simulations: varying number of species controlled Maximising net economic returns in mixed fisheries

21 Questions: Thank you Sean Pascoe: (Project Leader) Trevor Hutton Acknowledgements: 2015-Maximising net economic returns from a multispecies fishery is supported by funding from the FRDC (Fisheries Research & Development Corporation) on behalf of the Australian Government Other contributors: Neil Klaer, Roy Deng, Olivier Thebaud (IFREMER), Simon Viera, Pierre Lelong (Ecole P, France) Key reference: Pascoe, S., Hutton, T., Thebaud, O., Deng, R., Klaer, N., and S. Viera Setting economic target reference points for multiple species in mixed fisheries. FRDC Project No 2011/200. (93pp.) Maximising net economic returns in mixed fisheries